基于自适应滤波机理的脉冲激光近程探测云雾干扰滤波方法

Cloud Interference Filtering Method Based on Adaptive Filtering Mechanism for Pulsed Laser Short-Range Detection

针对云雾环境对激光近程探测系统测距精度的影响,提出了一种变步长自适应滤波方法。首先结合脉冲激光近程传输理论和Mie散射理论,建立脉冲激光云雾传输后向散射模型,在此基础上甄别、分离出云雾环境下脉冲激光回波的干扰信号;然后根据干扰信号的特征,采用自适应滤波方法滤除云雾干扰回波信号,研究了云雾干扰下激光回波的脉宽、峰值和回波时刻这三种随机干扰因素对滤波性能的影响;最后在实验室云雾环境下验证了所提滤波方法的效果。结果表明:在不同的激光回波脉宽、功率以及回波时刻下,所提自适应滤波方法具有良好的滤波效果和抗干扰性能,能有效提高脉冲激光近程探测系统在云雾环境下的测距精度。

Objective Laser short-range detection technology has been widely used in communications,aerospace,remote sensing and ranging.However,the precise identification of distance in the environment of cloud and fog interference is a difficult problem for laser short-range detection.It is easy to produce optical effects dominated by Mie scattering due to the narrow pulse width,high peak power and short pulse duration of the pulsed laser;the diameter of the cloud particles is close to the wavelength of the pulsed laser.This leads to changes in characteristics,such as the amplitude and pulse width of the laser echo signal,affecting the accuracy of laser short-range ranging.Because of the influence of cloud and fog interference on the accuracy of laser short-range ranging,several attempts have been made to adopt multi-system composites,multi-detector assistance and multi-beam detection methods.These methods use multiple detection units.The system is huge and complex;however,narrow pulse technology affects the system.Power consumption has strict requirements.Therefore,the above method cannot easily solve the problem of cloud and fog interference in a small laser short-range detection system.Methods Aiming at the problem of cloud and fog interference in a small laser short-range detection system,a pulsed laser cloud and fog transmission backscatter model is established based on the Mie scattering theory,and the interference echo signal is separated and extracted.According to the characteristics of the interference signal,a variable step adaptive filtering algorithm is proposed to suppress the interference of laser cloud and fog echo signal to the target signal.The experiment analyses the influence of three random factors of different laser cloud interference signal pulse width,peak power and time of appearance on the filtering effect.Results and Discussions When the target is in a cloud and fog environment,due to the short time interval between the scattered and target echoes,the two will overlap,and the echo signal will appear distorted,such as broadening;thus,severely impacting the accuracy of pulsed laser ranging.Since there are many uncertain factors in the interference of clouds and fog in the natural environment,the superimposed intensity of the interference signal and moment have strong randomness,and the pulse width(PW),peak intensity(PI)of the interference signal and the time interval between the interference signal and the target echo and other characteristic parameters cannot be described quantitatively.Additionally,it is not easy to filter or shield the above random interference signals by wavelet,high-order statistics and empirical mode decomposition(Fig.1).The amplitude and pulse width are set as 0.75 V and 5 ns,respectively.The signal amplitude of the cloud interference part is set as 0.4 V and the pulse width is set as 5,10,15 and 20 ns,respectively.The peak of the cloud interference signal appears 10 ns behind the peak of the laser echo signal in the cloudless environment.The amplitude of the interference signal of the laser echo signal processed using the proposed filtering method is compressed to about 0.056 V.The PW of the laser echo is expanded,and the phenomenon of wave peak effect is weakened.Additionally,the signal reduction degree and algorithm processing accuracy are improved(Figs.7 and 10).When the laser echo signal parameters are set in a cloudless environment,they are consistent with the above values.The PW of the cloud jamming signal is 15 ns;the amplitude is 0.2,0.3,0.4 and 0.5 V.The peak of the cloud jamming signal appears 10 ns after the peak of the laser echo signal in a cloudless environment.The amplitude of the laser echo signal processed using the proposed filtering method increases as the original peak value increases.When the original input peak value is 0.5 V,the filtered peak value is 0.072 V.In contrast,the filtered peak value is 0.049 V when the original input peak value is 0.2 V.The PW of the laser echo expands,and the phenomenon of wave peak effect slows down.The proposed filtering method can effectively target the laser echo cloud interference signals with different energies(Figs.8 and 11).When the laser echo parameters are set as above,the PW and amplitude of the fog jamming signal are 15 ns and 0.4 V,respectively.The peak of the fog jamming signal appeares at 20 ns,10 ns before and 10 ns after the peak of the fog jamming signal.The amplitude of laser echo interference signals processed using the proposed filtering method is suppressed below 0.056 V.The effective part of the laser echo signal containing cloud interference signal is equivalent to the laser echo signal without cloud interference.Therefore,it can be seen that the proposed filtering algorithm can effectively reduce the laser cloud interference signal at different moments(Figs.9 and 12).Conclusions In view of the influence of cloud environment on the ranging accuracy of pulsed laser short-range detection system,the characteristics of laser cloud interference echo signal are analysed.A variable step-size filtering algorithm with step-size memory effect is proposed based on the principle of LMS adaptive filtering to characterise laser cloud echo interference signals.To verify the anti-jamming performance of the proposed filtering method,we analyse three factors of random jamming,pulse width,peak intensity,and echo time interval.A comparative experiment of pulsed laser cloud environment interference filtering is conducted.The results show that the proposed adaptive filtering algorithm can effectively target random parameter cloud interference signals and improve the working stability of pulsed laser short-range detection systems in a cloud environment.